State of health estimation for lithium ion batteries based on an equivalent-hydraulic model: An iron phosphate application
| Autor: | Nathalie Job, Michel Kinnaert, Julien Schorsch, Luis D. Couto, Alexandre Léonard |
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| Rok vydání: | 2019 |
| Předmět: |
Battery (electricity)
Materials science Renewable Energy Sustainability and the Environment 020209 energy Lithium iron phosphate Energy Engineering and Power Technology chemistry.chemical_element 02 engineering and technology 021001 nanoscience & nanotechnology Power (physics) Extended Kalman filter chemistry.chemical_compound chemistry Control theory Colors of noise 0202 electrical engineering electronic engineering information engineering Lithium Iron phosphate Electrical and Electronic Engineering Diffusion (business) 0210 nano-technology |
| Zdroj: | Journal of Energy Storage. 21:259-271 |
| ISSN: | 2352-152X |
| DOI: | 10.1016/j.est.2018.11.001 |
| Popis: | A two-step approach for state-of-health (SOH) estimation of a lithium-ion (Li-ion) battery is developed. In the first step, state-of-charge (SOC) estimation is performed by a constrained extended Kalman filter (EKF) based on the so-called equivalent-hydraulic model. The latter model allows to characterize the internal battery state and main physical parameters while being suitable for on-line computation. The internal battery states are further exploited in the second step of the approach to obtain parameter-based SOH indicators that characterize the long term evolution of the diffusion and charge transfer processes associated to aging. Capacity and power fade indicators are determined by using notably an instrumental variable method in order to obtain unbiased parameter estimates in the presence of heteroscedastic colored noise. The methodology is validated on both simulation and experimental data for a lithium iron phosphate (LFP) half battery cell. This also provides insight on the properties of the LFP electrodes. |
| Databáze: | OpenAIRE |
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